Tourist behavior has a critical impact on the environmental sustainability of tourism. The hedonic nature of tourism and lack of an economic incentive make tourist behavior particularly hard to ...change. Making tourists behave more environmentally friendly would have substantial environmental benefits. This is the aim of the present study. Three alternative approaches are tested. The most successful approach—based on sharing monetary savings with guests—leads to a 42 percent change in one specific tourist behavior with negative environmental consequences. This new sharing-based approach significantly outperforms current approaches of increasing awareness of environmental consequences and of tourist ability to make a change. Tourism businesses should consider replacing current appeals with sharing-based schemes.
Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of ...specified keywords using an additional layer of latent variables which are referred to as topics. The R package topicmodels provides basic infrastructure for fitting topic models based on data structures from the text mining package tm. The package includes interfaces to two algorithms for fitting topic models: the variational expectation-maximization algorithm provided by David M. Blei and co-authors and an algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors.
RNA sequencing of time-course experiments results in three-way count data where the dimensions are the genes, the time points and the biological units. Clustering RNA-seq data allows to extract ...groups of co-expressed genes over time. After standardisation, the normalised counts of individual genes across time points and biological units have similar properties as compositional data. We propose the following procedure to suitably cluster three-way RNA-seq data: (1) pre-process the RNA-seq data by calculating the normalised expression profiles, (2) transform the data using the additive log ratio transform to map the composition in the D-part Aitchison simplex to a
-dimensional Euclidean vector, (3) cluster the transformed RNA-seq data using matrix-variate Gaussian mixture models and (4) assess the quality of the overall cluster solution and of individual clusters based on cluster separation in the transformed space using density-based silhouette information and on compactness of the cluster in the original space using cluster maps as a suitable visualisation. The proposed procedure is illustrated on RNA-seq data from fission yeast and results are also compared to an analogous two-way approach after flattening out the biological units.
Tourists bite off more than they can chew at hotel breakfast buffets. Food waste from hotel buffets means unnecessary food cost for hotels as well as an unnecessary burden on the environment. The ...present study measured food waste at a hotel breakfast buffet and identified the following guest and breakfast characteristics as being significantly associated with higher plate waste: more children in the guest mix, more Russians and less Austrians or Germans, fewer hotel guests in the breakfast buffet area as well as more buffet stations being set up. These insights contribute to knowledge on environmental sustainability in tourism, pointing to interesting market segments for targeting in high demand periods as well as promising target segments for interventions (e.g., families) and indicate that simple measures such as rearrangements of the breakfast room may reduce food waste.
Finite mixtures of von Mises-Fisher distributions allow to apply model-based clustering methods to data which is of standardized length, i.e., all data points lie on the unit sphere. The R package ...movMF contains functionality to draw samples from ?nite mixtures of von Mises-Fisher distributions and to ?t these models using the expectation-maximization algorithm for maximum likelihood estimation. Special features are the possibility to use sparse matrix representations for the input data, different variants of the expectation-maximization algorithm, different methods for determining the concentration parameters in the M-step and to impose constraints on the concentration parameters over the components. In this paper we describe the main ?tting function of the package and illustrate its application. In addition we compare the clustering performance of ?nite mixtures of von Mises-Fisher distributions to spherical k-means. We also discuss the resolution of several numerical issues which occur for estimating the concentration parameters and for determining the normalizing constant of the von Mises-Fisher distribution.
Destination image is among the most frequently measured constructs in empirical survey research. Academic tourism researchers tend to use multi-category scales, often referring to them as “Likert ...scales,” while industry typically uses “pick-any” measures. But which leads to results that are more valid? Findings from a large-scale experimental study show that a “forced-choice full binary” format (where respondents have to tick “yes” and “no” for each destination-attribute combination) performs better than both current preferred formats in academic and applied studies.
This paper identifies factors that are associated with higher levels of public acceptance for recycled and desalinated water. For the first time, a wide range of hypothesized factors, both of ...socio-demographic and psychographic nature, are included simultaneously. The key results, based on a survey study of about 3000 respondents are that: (1) drivers of the stated likelihood of using desalinated water differ somewhat from drivers of the stated likelihood of using recycled water; (2) positive perceptions of, and knowledge about, the respective water source are key drivers for the stated likelihood of usage; and (3) awareness of water scarcity, as well as prior experience with using water from alternative sources, increases the stated likelihood of use. Practical recommendations for public policy makers, such as key messages to be communicated to the public, are derived.
flexmix provides infrastructure for flexible fitting of finite mixture models in R using the expectation-maximization (EM) algorithm or one of its variants. The functionality of the package was ...enhanced. Now concomitant variable models as well as varying and constant parameters for the component specific generalized linear regression models can be fitted. The application of the package is demonstrated on several examples, the implementation described and examples given to illustrate how new drivers for the component specific models and the concomitant variable models can be defined.
Beta regression – an increasingly popular approach for modeling rates and proportions – is extended in various directions: (a) bias correction/reduction of the maximum likelihood estimator, (b) beta ...regression tree models by means of recursive partitioning, (c) latent class beta regression by means of finite mixture models. All three extensions may be of importance for enhancing the beta regression toolbox in practice to provide more reliable inference and capture both observed and unobserved/latent heterogeneity in the data. Using the analogy of Smithson and Verkuilen (2006), these extensions make beta regression not only “a better lemon squeezer” (compared to classical least squares regression) but a full-fledged modern juicer offering lemon-based drinks: shaken and stirred (bias correction and reduction), mixed (finite mixture model), or partitioned (tree model). All three extensions are provided in the R package betareg (at least 2.4-0), building on generic algorithms and implementations for bias correction/reduction, model-based recursive partioning, and finite mixture models, respectively. Specifically, the new functions betatree() and betamix() reuse the object-oriented flexible implementation from the R packages party and flexmix, respectively.
Changing default settings has proven to be a powerful approach to influencing consumer decisions without denying consumers the possibility of choosing freely. This is only the second study ...investigating the effectiveness of defaults in tourism, and the first testing also the combined effect of default changes and pro-environmental appeals in the context of changing room cleaning defaults in hotels from automatic daily cleaning (with the choice of opting out) to no daily routine cleaning (with the choice of opt-in and requesting a free room clean every day). Results from a quasi-experimental study conducted in a three-star city hotel suggest that the change in defaults significantly reduced room cleaning, with only 32% of room cleans requested on average. Adding a pro-environmental appeal to the change in defaults did not further reduce room cleaning overall, but has an effect on certain segments of hotel guests.
PDF
